On June 26, we received the news: MycoData was selected as one of the 15 finalist projects of Nano Impact 2026, the acceleration program by the Argentine Nanotechnology Foundation (FAN).

15
finalists
100+
applications
2/7
final pitch

What is Nano Impact 2026?

Nano Impact is a FAN program that identifies and supports science and technology projects with high impact potential. In this edition, they received applications from across the country and selected the 15 most promising projects to present at a final pitch before a jury of experts in innovation, investment, and technology.

What does this mean for MycoData?

Reaching this stage validates months of work: building a machine learning predictive model that helps researchers and laboratories estimate fungal bioremediation efficiency without experimenting blindly. Today our model achieves R²≈0.86 on real data extracted from over 1,200 scientific papers.

What we do:
MycoData analyzes scientific publication data and predictively estimates which fungus + contaminant + environmental conditions combination maximizes removal. We work with hydrocarbons, heavy metals, dyes, pharmaceuticals, and pesticides.

When and where is the final pitch?

The event will be on Thursday, July 2 at the Centro Cultural C3 (Godoy Cruz 2270, Buenos Aires). Each project has 5 minutes to present before the jury. We'll tell how MycoData can accelerate bioremediation research and reduce experimental costs.

A bit of the journey so far

  • ML pipeline: XGBoost model trained on 5,681 structured observations from scientific papers.
  • Taxonomic validation: 368 fungal species validated against GBIF.
  • Functional API: 6 endpoints for prediction, species recommendation, contaminant analysis, and general statistics.
  • Outreach: contacted over 80 researchers from LATAM and Spain for interviews and feedback.

What we need

This recognition gives us visibility, but the goal is to scale. We are looking for:

  • Laboratory collaborations for experimental validation of predictions.
  • Contact with early-stage investment funds interested in environmental deep tech.
  • Researchers who want to contribute data or co-author papers with the model.

If you made it this far, thank you for reading. See you at C3.

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